Evolutionary Computation(EC)has strengths in terms of computation for gait optimization.However,conventional evolutionary algorithms use typical gait parameters such as step length and swing height,which limit the tra...Evolutionary Computation(EC)has strengths in terms of computation for gait optimization.However,conventional evolutionary algorithms use typical gait parameters such as step length and swing height,which limit the trajectory deformation for optimization of the foot trajectory.Furthermore,the quantitative index of fitness convergence is insufficient.In this paper,we perform gait optimization of a quadruped robot using foot placement perturbation based on EC.The proposed algorithm has an atypical solution search range,which is generated by independent manipulation of each placement that forms the foot trajectory.A convergence index is also introduced to prevent premature cessation of learning.The conventional algorithm and the proposed algorithm are applied to a quadruped robot;walking performances are then compared by gait simulation.Although the two algorithms exhibit similar computation rates,the proposed algorithm shows better fitness and a wider search range.The evolutionary tendency of the walking trajectory is analyzed using the optimized results,and the findings provide insight into reliable leg trajectory design.展开更多
The current gait planning for legged robots is mostly based on human presets,which cannot match the flexible characteristics of natural mammals.This paper proposes a gait optimization framework for hexapod robots call...The current gait planning for legged robots is mostly based on human presets,which cannot match the flexible characteristics of natural mammals.This paper proposes a gait optimization framework for hexapod robots called Smart Gait.Smart Gait contains three modules:swing leg trajectory optimization,gait period&duty optimization,and gait sequence optimization.The full dynamics of a single leg,and the centroid dynamics of the overall robot are considered in the respective modules.The Smart Gait not only helps the robot to decrease the energy consumption when in locomotion,mostly,it enables the hexapod robot to determine its gait pattern transitions based on its current state,instead of repeating the formalistic clock-set step cycles.Our Smart Gait framework allows the hexapod robot to behave nimbly as a living animal when in 3D movements for the first time.The Smart Gait framework combines offline and online optimizations without any fussy data-driven training procedures,and it can run efficiently on board in real-time after deployment.Various experiments are carried out on the hexapod robot LittleStrong.The results show that the energy consumption is reduced by 15.9%when in locomotion.Adaptive gait patterns can be generated spontaneously both in regular and challenge environments,and when facing external interferences.展开更多
Based on the 7-link dynamic model in the sagittal plane and the 5-link dynamic model in the lateral plane, the parametric gait of the biped robot is designed using walking velocity, step length and height of the hip. ...Based on the 7-link dynamic model in the sagittal plane and the 5-link dynamic model in the lateral plane, the parametric gait of the biped robot is designed using walking velocity, step length and height of the hip. According to the condition of the stability, body swings forward and backward to dynamically balance in sagittal plane and the whole biped swings left and right to dynamically balance in lateral plane. And the genetic algorithm is applied to obtain the optimal parameters on condition of keeping dynamic stability and the minimizing of the value of the dynamic balance.展开更多
RHex-style robots can perform manifold moving gaits in different applications,but they have always faced a challenge of climbing up high obstacles.In this paper,the bionics-based gait optimization in an RHex-style rob...RHex-style robots can perform manifold moving gaits in different applications,but they have always faced a challenge of climbing up high obstacles.In this paper,the bionics-based gait optimization in an RHex-style robot is proposed for climbing steps at different heights,which even enables the robot to climb up the step with 4.2 times of the leg length.First,a thoracic flexion is designed in the robot,and an algorithm of adjusting body inclination is proposed to perform the rising stage after placing front legs on top of step,which can be applied in different RHex-style robots with different sizes.Especially,when the thoracic flexion is implemented,the robot can climb the higher step with the proposed algorithm.Second,to climbing the higher steps,a claw-shape legs-based algorithm is proposed for robot reaching the higher step and climbing it up.During the vital rising stage,when the front legs of the robot have reached the top of the step,the robot can bend the front body downward with its thoracic flexion like a cockroach,and then lift the front and middle legs alternately to move COM up and forward onto the step.The simulation analysis is utilized to verify the feasibility of the proposed algorithms.Finally,the step-climbing experiments at different heights are performed in our robot to compare with the existing works.The results of simulations and experiments show the superiority of the proposed algorithms for the improved robot due to climbing up the higher steps.展开更多
A parametric method to generate low energy gait for both single and double support phases with zero moment point（ZMP） stability is presented. The ZMP stability condition is expressed as a limit to the actuating torq...A parametric method to generate low energy gait for both single and double support phases with zero moment point（ZMP） stability is presented. The ZMP stability condition is expressed as a limit to the actuating torque of the support ankle, and the inverse dynamics of both walking phases is investigated. A parametric optimization method is implemented which approximates joint trajectories by cubic spline functions connected at uniformly distributed time knots and makes optimization parameters only involve finite discrete states describing key postures. Thus, the gait optimization is transformed into an ordinary constrained nonlinear programming problem. The effectiveness of the method is verified through numerical simulations conducted on the humanoid robot THBIP-I model.展开更多
基金This work was supported in part by the National Research Foundation of Korea(NRF)Grant funded by the Korean Government(MSIT)(No.NRF-2019R1A2C2084677)the 2021 Research Fund(1.210052.01)of UNIST(Ulsan National Institute of Science and Technology).
文摘Evolutionary Computation(EC)has strengths in terms of computation for gait optimization.However,conventional evolutionary algorithms use typical gait parameters such as step length and swing height,which limit the trajectory deformation for optimization of the foot trajectory.Furthermore,the quantitative index of fitness convergence is insufficient.In this paper,we perform gait optimization of a quadruped robot using foot placement perturbation based on EC.The proposed algorithm has an atypical solution search range,which is generated by independent manipulation of each placement that forms the foot trajectory.A convergence index is also introduced to prevent premature cessation of learning.The conventional algorithm and the proposed algorithm are applied to a quadruped robot;walking performances are then compared by gait simulation.Although the two algorithms exhibit similar computation rates,the proposed algorithm shows better fitness and a wider search range.The evolutionary tendency of the walking trajectory is analyzed using the optimized results,and the findings provide insight into reliable leg trajectory design.
基金Supported by National Key Research and Development Program of China(Grant No.2021YFF0306202).
文摘The current gait planning for legged robots is mostly based on human presets,which cannot match the flexible characteristics of natural mammals.This paper proposes a gait optimization framework for hexapod robots called Smart Gait.Smart Gait contains three modules:swing leg trajectory optimization,gait period&duty optimization,and gait sequence optimization.The full dynamics of a single leg,and the centroid dynamics of the overall robot are considered in the respective modules.The Smart Gait not only helps the robot to decrease the energy consumption when in locomotion,mostly,it enables the hexapod robot to determine its gait pattern transitions based on its current state,instead of repeating the formalistic clock-set step cycles.Our Smart Gait framework allows the hexapod robot to behave nimbly as a living animal when in 3D movements for the first time.The Smart Gait framework combines offline and online optimizations without any fussy data-driven training procedures,and it can run efficiently on board in real-time after deployment.Various experiments are carried out on the hexapod robot LittleStrong.The results show that the energy consumption is reduced by 15.9%when in locomotion.Adaptive gait patterns can be generated spontaneously both in regular and challenge environments,and when facing external interferences.
基金the Equipment Research Institute of the Fujitsu CompanyJapan
文摘Based on the 7-link dynamic model in the sagittal plane and the 5-link dynamic model in the lateral plane, the parametric gait of the biped robot is designed using walking velocity, step length and height of the hip. According to the condition of the stability, body swings forward and backward to dynamically balance in sagittal plane and the whole biped swings left and right to dynamically balance in lateral plane. And the genetic algorithm is applied to obtain the optimal parameters on condition of keeping dynamic stability and the minimizing of the value of the dynamic balance.
基金This work was supported in part by the National Natural Science Foundation of China(No.51605393)State Key Laboratory of Robotics and Systems(HIT)(SKLRS-2020-KF-13)Sichuan Science and Technology Program(2020YJ0035).
文摘RHex-style robots can perform manifold moving gaits in different applications,but they have always faced a challenge of climbing up high obstacles.In this paper,the bionics-based gait optimization in an RHex-style robot is proposed for climbing steps at different heights,which even enables the robot to climb up the step with 4.2 times of the leg length.First,a thoracic flexion is designed in the robot,and an algorithm of adjusting body inclination is proposed to perform the rising stage after placing front legs on top of step,which can be applied in different RHex-style robots with different sizes.Especially,when the thoracic flexion is implemented,the robot can climb the higher step with the proposed algorithm.Second,to climbing the higher steps,a claw-shape legs-based algorithm is proposed for robot reaching the higher step and climbing it up.During the vital rising stage,when the front legs of the robot have reached the top of the step,the robot can bend the front body downward with its thoracic flexion like a cockroach,and then lift the front and middle legs alternately to move COM up and forward onto the step.The simulation analysis is utilized to verify the feasibility of the proposed algorithms.Finally,the step-climbing experiments at different heights are performed in our robot to compare with the existing works.The results of simulations and experiments show the superiority of the proposed algorithms for the improved robot due to climbing up the higher steps.
基金the National Natural Science Foundation of China (No.60674017).
文摘A parametric method to generate low energy gait for both single and double support phases with zero moment point（ZMP） stability is presented. The ZMP stability condition is expressed as a limit to the actuating torque of the support ankle, and the inverse dynamics of both walking phases is investigated. A parametric optimization method is implemented which approximates joint trajectories by cubic spline functions connected at uniformly distributed time knots and makes optimization parameters only involve finite discrete states describing key postures. Thus, the gait optimization is transformed into an ordinary constrained nonlinear programming problem. The effectiveness of the method is verified through numerical simulations conducted on the humanoid robot THBIP-I model.
